Kvasice vs Baťov: result 2-4 and analysis
4. liga - Divizie EDivision E - 12Kick-off on October 19, 2024 at 12:30 PM (UTC)Městský Stadion Přerov, Přerov
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What was the result of Kvasice vs Baťov?
Baťov won 2-4 on October 19, 2024.
What is the recent form of both teams?
Over their last 12 matches in all competitions, Kvasice have 4 wins, 0 draws and 8 defeats; Baťov have 3, 2 and 10.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 13, 2024 | Tatran Všechovice(away) | 1-2 | 4. liga - Divizie E |
| Oct 5, 2024 | Šumperk(home) | 1-2 | 4. liga - Divizie E |
| Sep 27, 2024 | Hranice(away) | 1-3 | 4. liga - Divizie E |
| Sep 21, 2024 | Šternberk(home) | 1-0 | 4. liga - Divizie E |
| Sep 7, 2024 | Slavičín(home) | 5-1 | 4. liga - Divizie E |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 16, 2024 | Nové Sady(home) | 1-2 | 4. liga - Divizie E |
| Oct 12, 2024 | Bzenec(home) | 2-3 | 4. liga - Divizie E |
| Oct 5, 2024 | Vsetín(away) | 1-4 | 4. liga - Divizie E |
| Sep 27, 2024 | Holešov(home) | 0-2 | 4. liga - Divizie E |
| Sep 20, 2024 | Skaštice(home) | 0-1 | 4. liga - Divizie E |
What does the head-to-head say?
In the last meeting: 1 Kvasice win, 0 draws, 0 Baťov wins.
| Date | Score | Competition |
|---|---|---|
| Jul 28, 2024 | Kvasice 2-1 Baťov | Cup |
How many goals should we expect?
Kvasice score 1.4 and concede 1.9 goals per match over their last 12; Baťov score 1.0 and concede 1.9.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Kvasice | 1.4 | 1.9 | 2 | 9/12 | 10/12 |
| Baťov | 1.0 | 1.9 | 3 | 8/15 | 9/15 |
Over the last 12 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 16 | Baťov | 14 | 0 | 0 | 14 | 9 | 51 | 0 |
A question about Kvasice vs Baťov?
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How does Footlab AI compute this prediction?
The model combines both teams' Elo ratings (anchored by competition pool), their recent form weighted by opponent strength, home advantage and a Poisson matrix for scorelines. When bookmakers publish odds for the match, their consensus is built into the calculation: that is what proved most accurate on past matches. Its accuracy is measured continuously on the predictions actually published. Methodology and measured accuracy